Development and evaluation of a field-based high-throughput phenotyping platform

Physiological and developmental traits that vary over time are difficult to phenotype under relevant growing conditions. In this light, we developed a novel system for phenotyping dynamic traits in the field. System performance was evaluated on 25 Pima cotton (Gossypium barbadenseL.) cultivars grown in 2011 atMaricopa, Arizona. Field-grown plants were irrigated underwell watered andwater-limited conditions, withmeasurements taken at different times on 3 days in July andAugust. The systemcarried four sets of sensors tomeasure canopyheight, reflectance and temperature simultaneously on four adjacent rows, enabling the collection of phenotypic data at a rate of 0.84 ha h. Measurements of canopy height, normalised difference vegetation index and temperature all showed large differences among cultivars and expected interactions of cultivars with water regime and time of day. Broad-sense heritabilities (H)were highest for canopy height (H= 0.86–0.96), followed by the more environmentally sensitive normalised difference vegetation index (H = 0.28–0.90) and temperature (H = 0.01–0.90) traits. We also found a strong agreement (r= 0.35–0.82) between values obtained by the system, and values from aerial imagery and manual phenotyping approaches. Taken together, these results confirmed the ability of the phenotyping system to measure multiple traits rapidly and accurately. Additional keywords: cotton, genetics, Gossypium barbadense, phenomics, proximal sensing. Received 4 May 2013, accepted 18 July 2013, published online 5 September 2013